
% Table created by stargazer v.5.2 by Marek Hlavac, Harvard University. E-mail: hlavac at fas.harvard.edu
% Date and time: Fri, Apr 22, 2022 - 21:12:21
\begin{table}[!htbp] \centering 
  \caption{Full regression output for Table A-18} 
  \label{table_news_german_cl} 
\begin{tabular}{@{\hspace{-10pt}}l@{\hspace{-10pt}}cccccccc} 
\toprule 
 & \multicolumn{2}{c}{``germany''} & \multicolumn{2}{c}{German terms} & \multicolumn{2}{c}{Navy terms} & \multicolumn{2}{c}{Militarist groups} \\ 
 & (1) & (2) & (3) & (4) & (5) & (6) & (7) & (8)\\ 
\midrule  
\\[-2.1ex] $\Delta\textrm{IPW}_{1885}$ & 0.083$^{**}$ & 0.055 & 0.091$^{**}$ & 0.062$^{*}$ & $-$0.004 & 0.009 & $-$0.116$^{*}$ & $-$0.033 \\ 
  & (0.038) & (0.033) & (0.036) & (0.035) & (0.036) & (0.040) & (0.062) & (0.048) \\ 
 \addlinespace 
 const\_frac\_secondary $\times$ as.factor(year)1885 &  & $-$1.116 &  & $-$1.047 &  & 0.546 &  & 3.543$^{**}$ \\ 
  &  & (0.986) &  & (0.846) &  & (0.417) &  & (1.632) \\ 
 \addlinespace 
 const\_frac\_secondary $\times$ as.factor(year)1886 &  & $-$1.072 &  & $-$0.966 &  & 0.607 &  & 3.616$^{**}$ \\ 
  &  & (1.094) &  & (0.909) &  & (0.383) &  & (1.576) \\ 
 \addlinespace 
 const\_frac\_secondary $\times$ as.factor(year)1892 &  & $-$2.282$^{*}$ &  & $-$1.986$^{**}$ &  & 0.286 &  & 3.618$^{**}$ \\ 
  &  & (1.135) &  & (0.981) &  & (0.376) &  & (1.551) \\ 
 \addlinespace 
 const\_frac\_secondary $\times$ as.factor(year)1895 &  & $-$2.341$^{**}$ &  & $-$1.954$^{*}$ &  & 0.300 &  & 3.603$^{**}$ \\ 
  &  & (1.132) &  & (0.990) &  & (0.351) &  & (1.607) \\ 
 \addlinespace 
 const\_frac\_secondary $\times$ as.factor(year)1900 &  & $-$2.242$^{**}$ &  & $-$1.784$^{**}$ &  & 0.344 &  & 3.847$^{**}$ \\ 
  &  & (1.015) &  & (0.881) &  & (0.354) &  & (1.609) \\ 
 \addlinespace 
 const\_frac\_secondary $\times$ as.factor(year)1906 &  & $-$1.182 &  & $-$0.889 &  & 0.388$^{**}$ &  & 2.959$^{**}$ \\ 
  &  & (0.743) &  & (0.636) &  & (0.191) &  & (1.308) \\ 
 \addlinespace 
 const\_frac\_secondary $\times$ as.factor(year)1910 &  &  &  &  &  &  &  &  \\ 
  &  & (0.000) &  & (0.000) &  & (0.000) &  & (0.000) \\ 
 \addlinespace 
\midrule  
Initial Mf x year &  & x &  & x &  & x &  & x \\ 
Observations & 2,365 & 2,365 & 2,365 & 2,365 & 2,365 & 2,365 & 2,365 & 2,365 \\ 
R$^{2}$ & 0.740 & 0.743 & 0.758 & 0.760 & 0.861 & 0.861 & 0.514 & 0.521 \\ 
Adjusted R$^{2}$ & 0.673 & 0.676 & 0.695 & 0.697 & 0.825 & 0.825 & 0.389 & 0.395 \\ 
\bottomrule 
\textit{Note:}  & \multicolumn{8}{l}{$^{*}$p$<$0.1; $^{**}$p$<$0.05; $^{***}$p$<$0.01} \\ 
 & \multicolumn{8}{l}{\parbox[t]{0.5\textwidth}{
        Newspaper-level regressions. Dependent variable is number of uses of
        specified term per newspaper issue, standardized. All models include
        newspaper and year fixed effects. For newspapers in cities, $\Delta$IPW
        is calculated at the city-, not constituency-level. ``German terms'' are
        ``germany,'' ``kaiser,'' ``teuton,'' ``prussia,'' and ``fatherland,''
        ``Navy terms'' are ``navy,'' ``naval,'' ``dreadnought,'' ``battleship,''
        and ``fleet,'' ``Militarist groups'' are ``national service league'' and
        ``navy league.'' Standard errors clustered by county in parentheses.}} \\ 
\end{tabular} 
\end{table} 
